.claude/skills/team-protocols/SKILL.md
Shared protocols for multi-agent team coordination — execution model, named subagent spawning, file conflict prevention, developer/reviewer/lead protocols, role selection table. Referenced by multi-agent workflow skills.
npx skillsauth add avav25/ai-assets team-protocolsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Base protocols for coordinating a team of named subagents. This skill is not invoked directly — it is referenced by workflow skills via @team-protocols.
You are the Lead. You run in the main conversation thread and coordinate the team.
You MUST spawn each agent role as a NAMED subagent using the Agent tool. Do NOT execute agent work inline in the main thread. Each agent must be a separate, named subagent instance so the user can inspect each agent's context independently.
name parameter: e.g. name: "developer-java", name: "reviewer", name: "qa"subagent_type parameter matching the skill from the role selection tableSendMessage to communicate between agents — never simulate agent responses in the main threadIf you skip creating named subagents and instead do the work inline — that is a violation of this protocol.
Single instance per role — except Developers, where one instance per affected subproject stack is allowed (see role-selection-table.md). Do NOT spawn multiple Reviewers or multiple QA agents. Tasks within a role are processed strictly one at a time, sequentially.
Only ONE agent may edit files at any time. Agents take turns — never work on files in parallel.
Apply these protocols to all agents in the team:
developer-protocol.md — task implementation, self-verification, handoff format, review iterationsreviewer-protocol.md — independent verification, ghost change detection, issue reportinglead-protocol.md — orchestration, progress tracking, escalation, final summaryrole-selection-table.md — subproject-to-developer mapping and spawning rulesdevelopment
Use this skill when running the recurring (daily) knowledge-base rescan for a repo that already has knowledge/.knowledge-sync.yml — the main-thread dispatcher that reads the config, computes the git delta since last_scanned_sha, maps changed paths to affected doc areas, early-exits cheaply when nothing changed, then fans out one Agent(content-writer) per affected area, applies the propose/direct update policy, advances the baseline only on success, and writes an L4 run log — all with the G1 untrusted-content choke-point, secret-scan, deny-list, and budget controls woven in. For first-time setup use /knowledge-sync-init.
development
Use this skill when bootstrapping scheduled knowledge-base sync for a repo that has no knowledge/.knowledge-sync.yml yet — to run one-time setup that detects the knowledge_root from CLAUDE.md/AGENTS.md, maps doc areas to source globs, records opt-in external sources (Linear/Notion/WebFetch, all disabled by default), captures a baseline last_scanned_sha, sets the per-area update policy, generates or seeds knowledge/CONVENTIONS.md, provisions the L4 memory dir, and offers to register the daily routine. Routes ongoing recurring sync operations to /knowledge-sync.
tools
Use this skill when bootstrapping a target repository to be ai-skills-aware — on the first run of any ai-skills workflow in a fresh repo, when adopting the ai-skills plugin in an existing repo, or after upgrading to a plugin version that adds new memory paths or templates, including when the user does not say "init" but asks to "set up" or "onboard" the repo — to detect codebase type, create CLAUDE.md + AGENTS.md scaffolding, initialize the .ai-skills-memory/ directory tree from L1 templates, and configure .gitignore. Idempotent — safe to re-run. Accepts `--codebase-type <type>` and `--overwrite`. Not for re-initializing only memory — use `/memory-init` instead.
tools
Use this skill when extending, repairing, or improving plugin assets, when ingesting a `/feedback` report as a fix-cycle backlog, or when you do not remember which lower-level command is right for the job — the umbrella workflow for ai-skills plugin-asset authoring and maintenance: creating, auditing, fixing, improving, refactoring, and migrating skills, agents, rules, hooks, prompts, schemas, and rubrics inside the plugin. Auto-classifies the request, loads the right knowledge skills (`@prompt-engineering`, `@context-engineering`, `@team-protocols`), and spawns the right subagents (`prompt-engineer`, `system-architect`, `python-engineer`, `software-engineer`, `qa-engineer`, `eval-judge`) via the `Agent` tool.